[Numpy-discussion] Catching out-of-memory error before it happens

[Dinesh Vadhia]

I want to write a general exception handler to warn if too much data is being loaded for the ram size in a machine for a successful numpy array operation to take place.  For example, the program multiplies two floating point arrays A and B which are populated with loadtext.  While the data is being loaded, want to continuously check that the data volume doesn't pass a threshold that will cause on out-of-memory error during the A*B operation.  The known variables are the amount of memory available, data type (floats in this case) and the numpy array operation to be performed. It seems this requires knowledge of the internal memory requirements of each numpy operation.  For sake of simplicity, can ignore other memory needs of program.  Is this possible?
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